MATH 348 - Graphical Models

Semester Offered: Second Semester
Credits (Range): 3 Hours
Attribute: 3 NS, QPF

An introduction to graphical models and Bayesian networks. This course will emphasize both the theory and the applications of these probabilistic models. Topics may include: background in probability and graph theory, building models, tuning and updating models, decision making, algorithms to accomplish all of these tasks, and applications to machine learning, biology and medicine, statistics and other fields.
Instructor: K. Woods
Prerequisites & Notes
Prerequisite: Math 220.